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Decision-making under uncertainty - A field study of cumulative prospect theory

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  • Gurevich, Gregory
  • Kliger, Doron
  • Levy, Ori

Abstract

The presented research tests cumulative prospect theory (CPT, [Kahneman, D., Tversky, A., 1979. Prospect theory: An analysis of decision under risk. Econometrica 47, 263-291; Tversky, A., Kahneman, D., 1981. The framing of decisions and the psychology of choice. Science 211, 453-480]) in the financial market, using US stock option data. Option prices possess information about actual investors' preferences in such a way that an exploitation of conventional option analysis, along with theoretical relationships, makes it possible to elicit investor preferences. The option data in this study serve for estimating the two essential elements of the CPT, namely, the value function and the probability weighting function. The main part of the work focuses on the functions' simultaneous estimation under CPT original parametric specification. The shape of the estimated functions is found to be in line with theory. Comparing to results of laboratory experiments, the estimated functions are closer to linearity and loss aversion is less pronounced.

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  • Gurevich, Gregory & Kliger, Doron & Levy, Ori, 2009. "Decision-making under uncertainty - A field study of cumulative prospect theory," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1221-1229, July.
    • Handle: RePEc:eee:jbfina:v:33:y:2009:i:7:p:1221-1229
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    5. Dichtl, Hubert & Drobetz, Wolfgang, 2011. "Portfolio insurance and prospect theory investors: Popularity and optimal design of capital protected financial products," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1683-1697, July.
    6. Arisoy, Yakup Eser, 2010. "Volatility risk and the value premium: Evidence from the French stock market," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 975-983, May.
    7. Slawomir Kalinowski, 2020. "From expected utility theory to prospect theory: tracking down the experimental path after forty years," Operations Research and Decisions, Wroclaw University of Science Technology, Faculty of Management, vol. 30(4), pages 39-56.
    8. Daniel Cavagnaro & Mark Pitt & Richard Gonzalez & Jay Myung, 2013. "Discriminating among probability weighting functions using adaptive design optimization," Journal of Risk and Uncertainty, Springer, vol. 47(3), pages 255-289, December.
    9. Ming Che & Hongmei Wu & Yujia Li, 2023. "Do Fluctuations in Environmental Regulations Inhibit Investment: Evidence from China," IJERPH, MDPI, vol. 20(3), pages 1-15, January.
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    11. Brzezicka Justyna & Tomal Mateusz, 2023. "Estimation of the Utility Function of Money and Housing Based on the Cumulative Prospect Theory," Real Estate Management and Valuation, Sciendo, vol. 31(3), pages 83-92, September.
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    14. Martin Holmén & Felix Holzmeister & Michael Kirchler & Matthias Stefan & Erik Wengström, 2023. "Economic Preferences and Personality Traits Among Finance Professionals and the General Population," The Economic Journal, Royal Economic Society, vol. 133(656), pages 2949-2977.
    15. Beatrice D. Simo-Kengne & Kofi A. Ababio & Jules Mba & Ur Koumba, 2018. "Behavioral portfolio selection and optimization: an application to international stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(3), pages 311-328, August.
    16. Chen, Rongxin & Lepori, Gabriele M. & Tai, Chung-Ching & Sung, Ming-Chien, 2022. "Explaining cryptocurrency returns: A prospect theory perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    17. Zhong, Xiaoling & Wang, Junbo, 2018. "Prospect theory and corporate bond returns: An empirical study," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 25-48.
    18. Luís Alberto Godinho Coelho, 2014. "Portfolio Selection Optimization under Cumulative Prospect Theory – a parameter sensibility analysis," CEFAGE-UE Working Papers 2014_06, University of Evora, CEFAGE-UE (Portugal).
    19. Brünner, Tobias & Reiner, Jochen & Natter, Martin & Skiera, Bernd, 2019. "Prospect theory in a dynamic game: Theory and evidence from online pay-per-bid auctions," Journal of Economic Behavior & Organization, Elsevier, vol. 164(C), pages 215-234.
    20. Hwang, Soosung & Satchell, Steve E., 2010. "How loss averse are investors in financial markets?," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2425-2438, October.
    21. Sweksha Srivastava & Abha Aggarwal & Pooja Bansal, 2024. "Efficiency Evaluation of Assets and Optimal Portfolio Generation by Cross Efficiency and Cumulative Prospect Theory," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 129-158, January.
    22. Olivier L'Haridon & Craig S. Webb & Horst Zank, 2021. "An Effective and Simple Tool for Measuring Loss Aversion," Economics Discussion Paper Series 2107, Economics, The University of Manchester.
    23. Lei Wang & Qing Liu & Tongle Yin, 2018. "Decision-making of investment in navigation safety improving schemes with application of cumulative prospect theory," Journal of Risk and Reliability, , vol. 232(6), pages 710-724, December.
    24. Döbeli, Barbara & Vanini, Paolo, 2010. "Stated and revealed investment decisions concerning retail structured products," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1400-1411, June.
    25. Zhang, Yue-Jun & Lin, Jia-Juan, 2019. "Can the VAR model outperform MRS model for asset allocation in commodity market under different risk preferences of investors?," International Review of Financial Analysis, Elsevier, vol. 66(C).

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